VLSI single-chip (255,223) Reed-Solomon encoder with interleaver

The invention relates to a concatenated Reed-Solomon/convolutional encoding system consisting of a Reed-Solomon outer code and a convolutional inner code for downlink telemetry in space missions, and more particularly to a Reed-Solomon encoder with programmable interleaving of the information symbols and code correction symbols to combat error bursts in the Viterbi decoder

Thermo-viscoplastic analysis of hypersonic structures subjected to severe aerodynamic heating

A thermoviscoplastic computational method for hypersonic structures is presented. The method employs unified viscoplastic constitutive model implemented in a finite element approach for quasi-static thermal-structural analysis. Applications of the approach to convectively cooled hypersonic structures illustrate the effectiveness of the approach and provide insight into the transient inelastic structural behavior at elevated temperatures

Simulation-based power calculations for planning a two-stage individual participant data meta-analysis

BACKGROUND Researchers and funders should consider the statistical power of planned Individual Participant Data (IPD) meta-analysis projects, as they are often time-consuming and costly. We propose simulation-based power calculations utilising a two-stage framework, and illustrate the approach for a planned IPD meta-analysis of randomised trials with continuous outcomes where the aim is to identify treatment-covariate interactions. METHODS The simulation approach has four steps: (i) specify an underlying (data generating) statistical model for trials in the IPD meta-analysis; (ii) use readily available information (e.g. from publications) and prior knowledge (e.g. number of studies promising IPD) to specify model parameter values (e.g. control group mean, intervention effect, treatment-covariate interaction); (iii) simulate an IPD meta-analysis dataset of a particular size from the model, and apply a two-stage IPD meta-analysis to obtain the summary estimate of interest (e.g. interaction effect) and its associated p-value; (iv) repeat the previous step (e.g. thousands of times), then estimate the power to detect a genuine effect by the proportion of summary estimates with a significant p-value. RESULTS In a planned IPD meta-analysis of lifestyle interventions to reduce weight gain in pregnancy, 14 trials (1183 patients) promised their IPD to examine a treatment-BMI interaction (i.e. whether baseline BMI modifies intervention effect on weight gain). Using our simulation-based approach, a two-stage IPD meta-analysis has < 60% power to detect a reduction of 1 kg weight gain for a 10-unit increase in BMI. Additional IPD from ten other published trials (containing 1761 patients) would improve power to over 80%, but only if a fixed-effect meta-analysis was appropriate. Pre-specified adjustment for prognostic factors would increase power further. Incorrect dichotomisation of BMI would reduce power by over 20%, similar to immediately throwing away IPD from ten trials. CONCLUSIONS Simulation-based power calculations could inform the planning and funding of IPD projects, and should be used routinely

Architecture for time or transform domain decoding of reed-solomon codes

Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message

Diarrhea in HIV Infection

During the last decade, there has been an increase of immunocompromized patients all around the world; that mostly due to pandemic of Human Immunodeficiency Virus (HIV) infection. Chronic diarrhea as one of common symptoms in patients with HIV infection has different etiology compared to immunocompetent patients. Initial approach of diarrhea in HIV infection may be conducted by evaluating the temporal relationship between the development of diarrhea and the administration of antiretroviral, especially the protease inhibitor agents; which is then followed by fecal analysis/examination for pathogenic bacteria and protozoa as well as endoscopy examination. Biopsy examination of intestinal mucosa is necessary for HIV enteropathy or diarrhea due to microsporidia, which is confirmed further by electron microscopy. The etiology of chronic diarrhea in HIV patients may also different, depend on the cluster of differentiation count value of all patients. Based on such differences, it is necessary to have adequate approach, recognition and understanding in the management of chronic diarrhea, especially for HIV patients

Minimum sample size for external validation of a clinical prediction model with a continuous outcome.

Clinical prediction models provide individualized outcome predictions to inform patient counseling and clinical decision making. External validation is the process of examining a prediction model's performance in data independent to that used for model development. Current external validation studies often suffer from small sample sizes, and subsequently imprecise estimates of a model's predictive performance. To address this, we propose how to determine the minimum sample size needed for external validation of a clinical prediction model with a continuous outcome. Four criteria are proposed, that target precise estimates of (i) R2 (the proportion of variance explained), (ii) calibration-in-the-large (agreement between predicted and observed outcome values on average), (iii) calibration slope (agreement between predicted and observed values across the range of predicted values), and (iv) the variance of observed outcome values. Closed-form sample size solutions are derived for each criterion, which require the user to specify anticipated values of the model's performance (in particular R2 ) and the outcome variance in the external validation dataset. A sensible starting point is to base values on those for the model development study, as obtained from the publication or study authors. The largest sample size required to meet all four criteria is the recommended minimum sample size needed in the external validation dataset. The calculations can also be applied to estimate expected precision when an existing dataset with a fixed sample size is available, to help gauge if it is adequate. We illustrate the proposed methods on a case-study predicting fat-free mass in children

Calculating the sample size required for developing a clinical prediction model.

Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or prognosis in healthcare. Hundreds of prediction models are published in the medical literature each year, yet many are developed using a dataset that is too small for the total number of participants or outcome events. This leads to inaccurate predictions and consequently incorrect healthcare decisions for some individuals. In this article, the authors provide guidance on how to calculate the sample size required to develop a clinical prediction model

Direct Selective Laser Sintering of Tool Steel Powders to High Density: Part A - Effects of Laser Beam Width and Scan Strategy

This paper describes progress on the Direct Selective Laser Sintering of M2 and H13 tool steel powders, comparing this with previous and further observations on stainless steel powders. The distinguishing feature is the melting of single tracks and layers in deep powder beds. The paper focuses on changing characteristics of the melt pool (mass, volume, aspect ratio, stability) and laser-powder interactivity as the laser beam width, power and scan speed change. It also compares the melt pool of neighbouring tracks during single layer construction. Simulations from a computer model to predict melt pool shape and dimension show reasonable agreement with experimental results at low scan speeds (0.5mm/s). But unexpected increases in melt depth above 1.0mm/s have been observed, suggesting higher values and more variability in laser absorptivity than expected, even approaching 1.0 for the CO2 laser radiation used in this work.Mechanical Engineerin

Lifestyle interventions for type 2 diabetes management among migrants and ethnic minorities living in industrialized countries : a systematic review and meta-analyses

The objective of this systematic review was to determine the effectiveness of lifestyle interventions to improve the management of type 2 diabetes mellitus (T2DM) among migrants and ethnic minorities. Major searched databases included MEDLINE (via PubMed), EMBASE (via Ovid) and CINAHL. The selection of studies and data extraction followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. In the meta-analysis, significant heterogeneity was detected among the studies (I 2 >50%), and hence a random effects model was used. Subgroup analyses were performed to compare the effect of lifestyle interventions according to intervention approaches (peer-led vs community health workers (CHWs)-led). A total of 17 studies were included in this review which used interventions delivered by CHWs or peer supporters or combination of both. The majority of the studies assessed effectiveness of key primary (hemoglobin (HbA1c), lipids, fasting plasma glucose) and secondary outcomes (weight, body mass index, blood pressure, physical activity, alcohol consumption, tobacco smoking, food habits and healthcare utilization). Meta-analyses showed lifestyle interventions were associated with a small but statistically significant reduction in HbA1c level (-0.18%; 95% CI-0.32% to-0.04%, p=0.031). In subgroup analyses, the peer-led interventions showed relatively better HbA1c improvement than CHW-led interventions, but the difference was not statistically significant (p=0.379). Seven studies presented intervention costs, which ranged from US$131 to US$461 per participant per year. We conclude that lifestyle interventions using either CHWs or peer supporters or a combination of both have shown modest effectiveness for T2DM management among migrants of different background and origin and ethnic minorities. The evidence base is promising in terms of developing culturally appropriate, clinically sound and cost-effective intervention approaches to respond to the growing and diverse migrants and ethnic minorities affected by diabetes worldwide